Rollup Economics 2.0 In-depth exploration of Ethereum Rollup Economics

Author: Davide Crapis, Ethereum Researcher; Translation: LianGuaixiaozou

In February 2022, Barnabé proposed a rollup economics framework to consider resource pricing and value flow in economies dependent on L1. The framework introduces key concepts regarding the interaction of L2 MEV, L1 and L2 fees, as well as operator revenue and costs. This is a simple framework in a simple world: a continuously trained centralized rollup running in silos. Many changes have occurred in the past 18 months: shared ordering, decentralization, proof/data aggregation, rollup federations, governance, etc.

We propose a new framework that will help understand this new world, where rollups are ready for scalability. Many experiments are still ongoing, but we can already see the shadows of some patterns. We will analyze key patterns in the hope of providing a tool to help understand the direction of development and assist in discovering/answering unresolved questions. This article is the first in the “Rollup is Real” series. Subsequent articles in this series will delve deeper into aggregation and interoperability, decentralization and MEV elasticity, governance and resource allocation.

1. Revisiting Rollup Economics 1.0

The original rollup economics framework included three entities: users, rollup operators, and the base layer. It also had a simplified perspective on value flow: L2 fees and MEV, operator costs, and data publishing costs. This is a simple framework, but it is necessary to understand it first because from here, everything will quickly become more complex and interesting.

(Economic flow in the original rollup framework)

From this basic process, one can measure the surplus of the rollup protocol and infer related concepts such as MEV extraction and distribution, L2 issuance, L2 congestion fee allocation, and the time frame for maintaining a balanced or surplus budget for the rollup (the L2 ecosystem is a growing economy, and surplus operation may be useful, allocated by the community to public goods funds, development, and growth).

Rollup Protocol Surplus = L2 Fees – Operational Costs – Data Costs

The rollup protocol can control L2 fees (including congestion fees and MEV) and operational costs (including rewards and issuance to operators). Whether the protocol aims for balance or surplus, L2 operations require technical coordination to support optimal settings for L2 congestion fees, MEV extraction and redistribution, and reducing data costs through optimization and strategic releases. These are the main economic designs that different L2 ecosystems are attempting. In the future, protocols may want to reduce the uncertainty of data costs, for example, through the use of block space derivatives.

A significant change has occurred in the past 18 months. Similar to the situation with building L1 blocks, we have seen a categorization of more professional roles for rollup operators. As the economy grows, operators naturally become more specialized, which is a good thing because if we can design around it, the dispersion of focus will bring about a more resilient system. However, the design space is much larger now, so we need a new roadmap to guide us through this process.

2. Rollup is growing

As rollup matures and begins to move away from training wheels, the complexity within rollups themselves and between rollups of the same type (referred to as “rollup federations”) is increasing. The shared rollup architecture between rollups of the same type aims to improve “security” (through shared governance and community consensus), “efficiency” (through shared functionality and economies of scale), and “user experience” (through better interoperability and less fragmentation). At the same time, independent providers are developing infrastructure to offer one or more of these benefits to any rollup that chooses to use their services, regardless of the type. We call these “rollup coops”. We will start with updates to individual rollup economics and delve deeper into these models.

(An Ethereum rollup successfully detaching itself from training wheels)

(1) Indy rollup

Rollups are moving away from training wheels, improving security and decentralization. From an operational/economic perspective, the main costs include:

  • Ordering: This increases operational costs and (decentralized) economic costs to incentivize the sequencer.

  • Data availability (DA): Rollups must publish data to the base layer, incurring data costs, which was a major cost item discussed in the initial framework.

  • State verification (SV): Proving costs directly increase the operational costs of zk rollups.

In all of these cost areas, individual rollups face a significant trade-off between security and efficiency. For example, they may choose to use a data availability layer with lower security at a lower cost. Data publishing costs (referred to as data costs, although they include L1 computation costs associated with publishing) have historically been the highest cost item. EIP-4844 will soon be launched on Ethereum, significantly reducing this cost and providing the cost efficiency needed for rollups to scale and achieve new use cases. In the long run, data costs and the efficiency of related services may be achieved through aggregated offline innovations, unlocking economies of scale.

(The road to Ethereum’s scalability is paved with (recursive) aggregation)

Specific examples of aggregation include: shared ordering services; for optimistic rollups, an interesting idea is “shared batch publishing”, which can provide faster batch compression benefits, especially for smaller players, by offering faster data publishing at lower costs and higher security; for zk rollups, shared provers aggregating many SNARKs into a larger proof before publishing to L1 is one of the most exciting scalability benefits, particularly because they can be recursively aggregated, offering significant gains in efficient utilization of the L1 data market at the cost of more off-chain computation. One thing seems clear, either as part of a federation or as part of an economic alliance, rollups will eventually choose to adopt shared services.

One direction that the rollup ecosystem may take is to have more independent rollups closely integrated with L1. We haven’t seen many deployments yet, but there are at least two interesting architectures. One is a based rollup, which delegates its block ordering to L1, thus leveraging the L1 transaction supply network to extract MEV, but still retains the proxy to set L2 congestion fees. A more extreme example is a rollup enshrined in the Ethereum protocol itself. When we discuss the resilience and decentralization of rollup MEV, we will delve deeper into the economics of these models.

(2) Rollup Cooperatives

The first type of integration between two rollups is purely economic integration, such as cooperatives.

“A cooperative is an entity formed by a group of individuals with a common goal or working together to achieve a common goal (such as profit or savings).” – Wikipedia

In its simplest form, a rollup has a service consortium purchasing agreement. Suppose there is a shared batch publication service, the rollup can subscribe to this service and obtain lower data publication costs. There can also be deeper economic integration, for example, a shared ordering service can improve cost efficiency and make transactions easier to settle automatically between rollups, thereby reducing barriers to cross-rollup transactions. This mindset is similar to an economic association like the European Economic Community (i.e., the EU before becoming a political entity) or other similar common market associations.

(Economic flow in the rollup community using shared services)

We can use intermediate service providers (such as shared sorters, publishers, or even prover services) to expand the simple model of an independent rollup economy. In this case, there are two new economic impacts on the rollup ecosystem.

  • Cost structure: Rollup operators’ costs now include operational costs, service costs, and data publication costs.

  • Shared service economy: New entities need to achieve budget balance.

Shared service surplus = rollup A service costs + rollup B service costs – operational costs – shared service data costs

An example of such a service is the Espresso sorter, which is a shared service for sorting and publishing, specifically for shared batch publishing or shared proofs. In all these cases, shared services also bring two important economic issues.

  • Allocation of L2 service costs: Total service costs need to be allocated among the rollups adopting the shared service in an economic and fair manner.

  • Decentralization of shared services: Achieving an appropriate level of decentralization between performance and robustness depending on the specific service. It has a lower threshold than the base layer, but it includes incentives and MEV management.

(3) Rollup Federation

Rollup federations differ from cooperatives in that they have both economic integration and some form of political integration. Their mindset is that of a national alliance.

“A federation is a cluster of states that delegates some sovereignty to a central governing authority that enforces certain laws and regulations.” – Wikipedia

Technically, political integration is achieved through shared bridging, but it also requires a shared governance system (the central governing authority of the federation). Here, we will set aside considerations of politics and governance and assume the existence of shared bridging, focusing instead on the implied economic relationships. This rollup federation architecture is emerging in all major rollup systems, which are becoming platforms for deploying interoperable rollups (as opposed to sub-rollups, see RaaS and L3 in the next section).

(Emerging architecture of major L2 ecosystems)

For example, Optimism Superchain, Polygon 2.0, StarkWare SHARP, zkSync Hyperchains, and other related projects share similar patterns in their architectures. We summarize them in the following diagram, making a realistic assumption to isolate the impact, namely that the federated rollup autonomously selects shared services and does not incur direct data publishing costs.

(Rollup federation shared services and bridging to the base layer)

Shared bridging introduces additional economic variables. In particular, native L2 tokens such as OP in the optimism ecosystem provide important decision-making power through governance, allowing for the allocation of resources, roles, and economic flows within the ecosystem (e.g., OP governance is a governance experiment based on mixed-token identities). Once the rollup technology stack matures and primary security issues are resolved, the next challenge is robustness, which may involve some degree of decentralization.

When rollups consider building decentralized services (for ordering, proving, or verifying), they will need to run consensus protocols. At this point, ecosystems of sufficient scale see an opportunity to “upgrade” their native tokens into productive assets, as planned by Polygon 2.0 with the POL upgrade. This is not the only way to achieve decentralized L2 services, as Ethereum L1 can leverage better security attributes to achieve this. However, for larger ecosystems, using native tokens may be an attractive direction as they want to retain more internal control/governance over their services, as well as related reward/incentive mechanisms.

Native token value change = Demand change – Net issuance

Native tokens are important economic tools that help guide the L2 ecosystem/economy. Token issuance can be used to reward service providers and provide funding for ecosystem support projects or public goods. However, when native tokens are used to support decentralization through native proof-of-stake protocols, their security may be reduced with more dilution. Even if native tokens are only used for governance, excessive dilution can also lead to more restricted token holders selling their tokens, potentially resulting in concentration of ownership. Therefore, there seems to be an important need for a token issuance schedule that is coordinated with demand growth. Finally, another important consideration is that making the L2 economy more dependent on native tokens (as opposed to ETH) also reduces its robustness against certain failure modes, as exiting L1 may not be an option. In extreme cases, L2 is still protected by Ethereum but loses the security provided by ETH as external funding.

3. More Layers

Around specific applications or customized execution environments (settling on the underlying layer), there have also been numerous active development activities. These development activities are typically aimed at applications that require low execution costs, are easy to deploy, and are willing to sacrifice security. Think of games, social media, and NFT products that do not need to bootstrap their own service economy or attract/ensure a large amount of liquidity.

The development areas are diverse, including L3, validums, and rollup as a service (RaaS) platforms. For example, Arbitrum Orbit is a platform that can deploy L3 chains on Arbitrum L2 (One or Nova) and has a certain degree of configurability, such as choosing an Arbitrum-authorized data availability committee (DAC) instead of Ethereum L1 as the data availability layer. StarkNet and other zk rollup projects have also been trying to deploy L3. An extreme example in the direction of ease of deployment is AltLayer or Caldera, which deploy “customizable” rollups through no-code solutions and give users agency to make their own security and efficiency trade-offs.

(Economic flow of L3 systems)

We focus on L3 systems. This is actually an additional layer on top of L2. From the perspective of L2 rollups, this is an additional source of fees for L2. L3 is a new entity in the rollup ecosystem with its own budget constraints:

  • L3 revenue can come from game charges and subscriptions, or other mechanisms such as NFT revenue sharing.

  • L3 costs include the operation costs of the system and the L2 fees for computation/data. These costs can be directly borne by L3 or, in terms of management services, paid for by RaaS platforms, another service provider that must balance its budget.

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